Doc. Ing. Ivo Bukovský, Ph.D.
Associate Professor, Division Head (U12110.3)
U 12110 Department of Instrumentation and Control Engineering
Division of Automatic Control and Engineering Informatics
Faculty of
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IEEE CIS
Neural Networks Technical Committee
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E-mail: Ivo.Bukovsky@fs.cvut.cz
http://users.fs.cvut.cz/ivo.bukovsky/ (home web)
http://control.fs.cvut.cz/cz/lide/bukovsky-ivo (department web)
http://www.fs.cvut.cz/~bukovsky
Phone: +420 22435 2529, (from US and
Research Interests:
·
Adaptive novelty detection:
Learning Entropy
·
Adaptive algorithms and
neural networks for complicated dynamic systems and signals
·
Multi-scale analysis approaches to signal processing and
dynamic systems
·
Time series analysis and
prediction
·
Nonlinear adaptive control
·
Fuzzy-logic rule based systems for modeling and
evaluation of complex dynamic systems:
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Applications of Type-2 Fuzzy
Sets.
Publications … click to see the full list of my
publications
New
[1]
Bukovsky, I., Homma, N., et al: "A Fast Neural Network Approach to Predict Lung Tumor Motion
during Respiration for Radiation Therapy Applications", BioMed Research International, issue Radiation Oncology and Medical Physics (ROMP) (open
Access) DOI: 10.1155/2738, September, 2014. (10/09/2014 article in press - to
appear)
Habilitation Thesis
[2]
Bukovsky, I.: Nonconventional Neural Architectures and their Advantages
for Technical Applications,
Faculty of Mechanical Engineering,
Ph.D. Thesis
[3]
Bukovsky, I. : Modeling of Complex Dynamic Systems by Nonconventional Artificial Neural
Architectures and Adaptive Approach to Evaluation of Chaotic Time Series, Ph.D. THESIS, Faculty of Mechanical
Engineering, Czech
Tutorial
[4]
Ivo Bukovsky, Jiri Bila, Madan M. Gupta, and Zeng-Guang Hou: NEW NEURAL ARCHITECTURES AND NEW ADAPTIVE EVALUATION OF
CHAOTIC TIME SERIES, TUTORIAL for
2008 IEEE
International Conference on AUTOMATION AND LOGISTICS, August 31 2008,
2:00pm – 5:00pm,
(Download
pdf from IEEE CIS Multimedia Tutorials Center)
Book Chapters
[5]
Bukovsky, I., Bila. J: “Adaptive Evaluation of Complex Dynamic Systems using
Low-Dimensional Neural Architectures”, in Advances in Cognitive Informatics and Cognitive Computing,
Series: Studies
in Computational Intelligence,
Vol. 323/2010, eds. D. Zhang, Y. Wang, W. Kinsner, Springer-Verlag Berlin Heidelberg, 2010,
ISBN: 978-3-642-16082-0, pp.33-57.
[6]
Gupta, M., M., Bukovsky,
[7]
Rodriguez , R., Bukovsky,
[8]
Bukovsky, I., Bila, J., Gupta, M.,
M, Hou, Z-G., Homma, N.,.: “Foundation and Classification of Nonconventional Neural
Units and Paradigm of Nonsynaptic Neural Interaction”
in Discoveries and Breakthroughs in Cognitive Informatics and
Natural Intelligence within the series of the
Advances in Cognitive Informatics and Natural Intelligence (ACINI), ed. Y.
Wang, IGI Publishing, Hershey PA,
USA, 2010. ISBN: 978-1-60566-902-1, pp.508-523.
[9]
Gupta, M., M, Homma, N., Hou,
Z-G., Solo, M., G., Bukovsky,
Journal Papers
[10] A. Vagaská, P.
Michal,
[11]
Bukovsky, I.: ¨Learning
Entropy: Multiscale Measure for Incremental Learning¨, journal of Entropy, special issue
on Dynamical Systems,, ISSN
1099–4300, 2013, 15(10), 4159-4187;
doi:10.3390/e15104159
[12]
Bukovsky,
[13]
Bila, J., Jura, J., Pokorny, J., Bukovsky,
[14]
Rodriguez , R., Bukovsky,
[15]
Homma, N., Kato,
S., Goto, T., Bukovsky,
[16]
Bukovsky, I., Hou, Z-G., Bila, J., Gupta, M., M.: “Foundation of Nonconventional Neural Units and their
Classification”, International Journal of Cognitive Informatics and Natural
Intelligence (IJCiNi),
2(4), October-December 2008, IGI Publishing, Hershey PA, USA, ISSN 1557-3958,
pp.29-43.
Local Journal Papers
[17]
Bukovsky, I., Rodriguez, R., Bila,
J., Homma, N.: “Prospects of Gradient
Methods for Nonlinear Control”, Strojárstvo Extra, MEDIA/ST,
s.r.o. publishing house, 2012, ISSN 1335-2938.
[18]
Bukovsky, I., Homma, N.: “Dynamic Backpropagation and
Prediction (Dynamický backpropagation
a predikce)” (in Czech), In: Automatizace, Vol. 53, No. 1-2, Prague, Czech
Republic, Jan-Feb 2010, ISSN 0005-125X, pp.61-66.
[19]
Bukovsky, I., Homma, N.: “Dynamic Backpropagation
(Dynamický backpropagation)”
(in Czech), In: Automatizace,
Vol. 52, No. 10,
[20]
Bukovsky, I., Bila, J., Gupta,
M., M.: “Linear Dynamic
Neural Units with Time Delay for Identification and Control" (in Czech),
In: Automatizace, Vol. 48, No. 10, Prague, Czech
Republic, Oct 2005, ISSN 0005-125X, pp. 628-635.
[21]
Bíla, J., Vitkaj, J., Musil, M., Bukovsky, I.: “Some Limits of Neural Networks Use in Diagnostics” (in
Czech),In.: Automatizace,
vol. 46, issue 11, 2003,
Selected Conference Papers
[22] Ivo Bukovsky, Cyril
Oswald, Matous Cejnek,
Peter M. Benes:" Learning Entropy for Novelty Detection A
Cognitive Approach for Adaptive Filters", accepted paper for Sensor
Signal Processing for Defence (SSPD) Conference 2014, Edinburgh, UK,
Sept. 8-9, 2014
[23] Ivo Bukovsky, Noriyasu
Homma, Matous Cejnek and
Kei Ichiji: "Study of Learning Entropy for Novelty Detection in Lung
Tumor Motion Prediction for Target Tracking Radiation Therapy", The 2014 International Joint Conference on Neural
Networks (IJCNN 2014), IEEE WCCI 2014,
[24] Peter
Benes and Ivo Bukovsky:
"Neural Network Approach to Hoist Deceleration Control",
The 2014
International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI 2014,
[25] Peter
Michal, Jan Pitel, Alena Vagaska and Ivo Bukovsky: "Application of Neural Networks to Evaluate
Experimental Data of Galvanic Zincing", The 2014
International Joint Conference on Neural Networks (IJCNN 2014), IEEE WCCI 2014,
[26]
Bukovsky, I., Kinsner, W., Bila, J.: „Multiscale Analysis Approach for Novelty
Detection in Adaptation Plot“, 3rd
Sensor Signal Processing for Defence 2012 (SSPD 2012), Imperial College London, UK, September 24-27, 2012, doi: 10.1049/ic.2012.0114, E-ISBN: 978-1-84919-712-0.
[27] Witold Kinsner, Simon Haykin, Yingxu Wang, Witold Pedrycz, Ivo Bukovsky,
Bernard Widrow, Andrzej Skowron, Piotr Wasilewski, and Menahem Friedman:
“Challenges in Engineering Education of
Cognitive Dynamic Systems”, Proceedings of
the Canadian Engineering Education Association
2012 (conf. CEEA12).
[28] Bukovsky, I., Kolovratnik, M.: “Neural Network Model for Prediction of NOx at Coal-Powder Powerplant Mělník
[29] Bukovsky,
[30]
Bukovsky,
[31]
Ichiji, K., Homma,
N., Bukovsky,
[32] Bukovsky, I., Lepold, M., Bila J.: “Quadratic Neural Unit and its Network in Validation of
Process Data of Steam Turbine
[33] Bukovsky,
[34]
Bukovsky, I., Homma,
N., Smetana, L., Rodriguez, R., Mironovova M., Vrana S.,: “Quadratic Neural Unit is a Good Compromise
between Linear Models and Neural Networks for Industrial Applications”, ICCI 2010 The 9th IEEE International Conference on Cognitive Informatics, Tsinghua
University, Beijing, China, July 7-9, 2010.
[35] Bukovsky, I., Anderle, F.,
Smetana, L.,: “Quadratic
Neural Unit for Adaptive Prediction of Transitions among Local Attractors of
Lorenz System”, 2008 IEEE
International Conference on AUTOMATION AND LOGISTICS,
[36] Bukovsky, I., Bila, J.: “Adaptive Evaluation
of Complex Time Series using Nonconventional Neural Units“, ICCI 2008, The
7th IEEE International Conference on COGNITIVE INFORMATICS,
[37] Simeunovic , G., Bukovsky, I.: “The Implementation of the Dynamic-Order-Extended
Time-Delay Dynamic Neural Units to Heat Transfer System Modelling”,
16th International
Conference on NUCLEAR ENGINEERING (ICONE 16 ASME),
[38] Bukovsky, I., Hou, Z-G., Gupta, M., M., Bila,
J.: “Foundation of Notation and Classification of Nonconventional Static and
Dynamic Neural Units”, ICCI
2007, The 6th IEEE International Conference on
COGNITIVE INFORMATICS,
[39] Bukovsky,
… click to see the full list of my publications
Research Project Reports
[40]
Bukovský, I.: Křehlík, K.: Testy neuronového modelu kotle elektrárny
Mělník I, research report (Výzkumná
zpráva č. 8-ZI00069/ E06) for I. & C. Energo, a.s. U12110, Faculty of
Mechanical Engineering, Czech Technical University in Prague, 2011, 61 pages.
[41]
Bukovský, I.: Křehlík, K.: Otestování metody extrapolace pyrometrických měření na základě
neuronových sítí,
research report # 7-ZI00069/E05 for I. & C. Energo,
a.s., U12110, Faculty of Mechanical Engineering,
Czech Technical University in Prague, 2011, 16 pages.
[42]
Bukovsky, I.: Návrh regulačního algoritmu kotle na základě neuronového
modelu elektrárny Mělník I, research report (Výzkumná zpráva č. 8-ZI00069/
E02) for I. & C. Energo, a.s.
U12110, Faculty of Mechanical Engineering, Czech Technical University in
Prague, 2011, 6 pages.
[43]
Bukovsky, I..: Dynamické neuronové sítě pro nestacionární modely a validaci veličin energetických procesů (Dynamical Neural Networks for Nostationary
Models and for Validation of Variables of Energetic Processes), Výzkumná zpráva č. 4 pro I. &
C. Energo, a.s. U12110,
Faculty of Mechanical Engineering, Czech Technical University in Prague, 2010,
40 pages.
[44]
Bukovsky, I.: Návrh metodiky extrapolace obrazců řezu spalovací komorou (Development of Extrapolation Method for Thermal
Images in Combustion Chamber), Výzkumná zpráva č. 5 pro I. &
C. Energo, a.s. U12110,
Faculty of Mechanical Engineering, Czech Technical University in Prague, 2010,
6 pages.
[45]
Bukovsky, I.; Nonconventional neural networks and
validation of process data, research report for I & C Energo, a.s. U12110, Faculty of
Mechanical Engineering, Czech Technical University in Prague, 2009, 93 pages.
[46] Bukovsky,
[47] Bukovsky,
[48] Bukovsky,
I. : Development of Higher-Order
Nonlinear Neural Units as a Tool for Approximation, Identification and Control
of Complex Nonlinear Dynamic Systems and Study of Their Application Prospects
for Nonlinear Dynamics of Cardiovascular System, Final report from
scientific research under NATO Science Fellowships at the Intelligent System
Research Laboratory at the University of Saskatchewan in Canada from April to
October 2003 partially supported by Internal Grant of Czech Technical
University (IGS #CTU0304112), 2003,32 pages.
… click to see the full list of my publications
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IEEE CIS Neural Networks Technical Committee (2007, 08, 09, 10, 11,12)
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IEEE CIS NNTC
Task Force on Education (chair 2009, 10, 11, 12)
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IEEE CIS Student
Activity Subcommittee (Vice Chair 2010, 11, 12)
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Graduate Student
Research Grants (2011)
Workshop Organization
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CompSens 2011, IEEE Workshop on Merging Fields of
Computational Intelligence and Sensor Technology, within the IEEE Symposium Series on Computational Intelligence 2011, Paris,
2011.
Special Session Organization
-
I.
Bukovsky, T. Wagner, J. Pitel,:
IEEE CompSens 2013, session on Merging Fields of Computational
Intelligence and Sensor Technology, within the IEEE Symposium Series on Computational Intelligence 2013, Singapore,
2013.
-
S.Y. Fu, N. Homma, I. Bukovsky,
A.M.G. Solo, and M.M. Gupta: Biologically
Inspired Sensing, Computing and Control Session, within the The seventh International Conference on Intelligent Systems and
Knowledge Engineering (ISKE2012), Beijing, China, 2012.
Editorial
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A/E IEEE
Transactions on Neural Networks, 2011,12,13.
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Cognitive
and Neural Aspects in Robotics 2011, annual issue of Journal of Robotics, Hindawi Publishing Corporation (Jan 2012)
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Cognitive
and Neural Aspects in Robotics with Applications 2010, special issue on Journal of Robotics, Hindawi Publishing Corporation
Conference Activities
Journals Reviews
- IEEE Transactions on Neural Networks, 2010,11,12
- Nuclear Engineering and Design, 2009
- Soft Computing, 2009
Book chapter reviews
- Advances in Cognitive Informatics, LNAI, 2009 (1x)
- Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications, 2009 (1x)
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Project review for NSERC,
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Consulting the use of neural networks and nonlinear
methods for classification of traffic data for ELTODO EG, a.s.,
2008
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www.konmep1.eu -
International visiting research arrangements for PhD students